Mixed Effects Model and Differential Abundance Analysis of Infants with HIV
Akshay Iyer
2024-02-08
Study Design and Aims
Insert model information here - How was data gathered, from whom?
- Differential Abundance Analysis - explanation
- Mixed Effect Models Explanation
Differential Abundance Analysis
The “limma-voom” methodology is an analytical approach developed for the analysis of gene expression data, particularly from microarray and RNA sequencing experiments. It combines two components, “limma” (Linear Models for Microarray Data) and “voom” (Variance Modeling at the Observation Level), to identify differentially expressed genes across different experimental conditions.
Limma uses linear models to assess differential expression, enabling the comparison of multiple groups or experimental conditions. limma is notable for its ability to handle complex experimental designs, incorporate multiple sources of variation, and efficiently manage the high-dimensional data typical of gene expression studies.
Here we have adapted the model to give us fold-change for flow cytometry data, instead of differential expression, this is analysing differential abundance.
Normalisation with VOOM
voom estimates the mean-variance relationship of the log-transformed counts, transforming the count data to a continuous scale that is suitable for linear modeling. It also assigns a weight to each observation, reflecting the reliability of each marker’s expression measurement, which improves the statistical power and accuracy of differential abundance analyses.
The following is essentialy how the data was normalized for downstream analysis
All Populations Combined
Monocytes
Dendritic Cells
NK Cells
T and B Cells
Volcano Plots and Fold Change
Volcano Plots are used to provide a visual representation of the fold change between HEI and HEU conditions. Positive foldchange is an increase in HEI with respect to HEU and negative fold change is the oposite. Multiple testing was performed and significant populations (padj <0.05) are colored in red.
All Populations Combined
Fold Change
Volcano Plot
Monocytes
Fold Change
Volcano Plot
Dendritic Cells
Fold Change
Volcano Plot
NK Cells
Fold Change
Volcano Plot
T & B Cells
Fold Change
Volcano Plot
Covariates Analysis
This analyses the covariate effect size on each cell population ranked by effect size.The star indicates significance.
Relationship with Viral Titre
Combined Populations
Monocytes
NK Cells
Dendritic Cells
T & B Cells
Relationship with HIV Status
Combined Populations
Monocytes
NK Cells
Dendritic Cells
T & B Cells
Relationship with Age
Combined Populations
Monocytes
NK Cells
Dendritic Cells
T & B Cells
Relationship with Gender
Combined Populations
Monocytes
NK Cells
Dendritic Cells
T & B Cells
